Diagnosing the benign paroxysmal positional vertigo via 1D and deep-learning composite model.

Journal: Journal of neurology
Published Date: Aug 1, 2023

Abstract

BACKGROUND: Benign Paroxysmal Positional Vertigo (BPPV) is the leading cause of vertigo, and its characteristic nystagmus induced by positional maneuvers makes it a good model for Artificial Intelligence (AI) diagnosis. However, during the testing procedure, up to 10 min of indivisible long-range temporal correlation data are produced, making the AI-informed real-time diagnosing unlikely in clinical practice.

Authors

  • Peixia Wu
    Nursing Department, Eye & ENT Hospital, Fudan University, Shanghai, China.
  • Xuebing Liu
    Department of Computer Science and Engineering, Jeonbuk National University, Jeonju, South Korea.
  • Qi Dai
    The First Clinical Medical College, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Jiaoda Yu
    ENT Institute and Otorhinolaryngology Department of Eye and ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
  • Jieli Zhao
    ENT Institute and Otorhinolaryngology Department of Eye and ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
  • Fangzhou Yu
    Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China.
  • Yaoqian Liu
    ENT Institute and Otorhinolaryngology Department of Eye and ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
  • Yongbin Gao
    School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China.
  • Huawei Li
    Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China.
  • Wenyan Li
    School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social risk Governance in Health, Chongqing Medical University, Chongqing 400016, China.

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